The present invention relates to the field of digital cameras and digital image processing and, more particularly, to designs and techniques for reducing processing requirements and therefore size of digital cameras.
Today, digital imaging, particularly in the form of digital cameras, is a prevalent reality that affords a new way to capture photos using a solid-state image sensor instead of traditional film. A digital camera functions by recording incoming light on some sort of sensing mechanisms and then processes that information (basically, through analog-to-digital conversion) to create a memory image of the target picture. A digital camera's biggest advantage is that it creates images digitally thus making it easy to transfer images between all kinds of devices and applications. For instance, one can easily insert digital images into word processing documents, send them by e-mail to friends, or post them on a Web site where anyone in the world can see them. Additionally, one can use photo-editing software to manipulate digital images to improve or alter them. For example, one can crop them, remove red-eye, change colors or contrast, and even add and delete elements. Digital cameras also provide immediate access to one's images, thus avoiding the hassle and delay of film processing. All told, digital photography is becoming increasingly popular because of the flexibility it gives the user when he or she wants to use or distribute an image.
The defining difference between digital cameras and those of the film variety is the medium used to record the image. While a conventional camera uses film, digital cameras use an array of digital image sensors. When the shutter opens, rather than exposing film, the digital camera collects light on an image sensor, a solid state electronic device. The image sensor contains a grid of tiny photosites that convert light shining on them to electrical charges. The image sensor may be of the charged-coupled device (CCD) or complementary metal-oxide semiconductor (CMOS) varieties. Most digital cameras employ charge-coupled device (CCD) image sensors, but newer cameras are using image sensors of the complimentary metal-oxide semiconductor (CMOS) variety. Also referred to by the acronym CIS (for CMOS image sensors), this newer type of sensor is less expensive than its CCD counterpart and requires less power.
During camera operation, an image is focused through the camera lens so that it will fall on the image sensor. Depending on a given image, varying amounts of light hit each photosite, resulting in varying amounts of electrical charge at the photosites. These charges can then be measured and converted into digital information that indicates how much light hit each site which, in turn, can be used to recreate the image. When the exposure is completed, the sensor is much like a checkerboard, with different numbers of checkers (electrons) piled on each square (photosite). When the image is read off of the sensor, the stored electrons are converted to a series of analog charges which are then converted to digital values by an Analog-to-Digital (A-to-D) converter, which indicates how much light hit each site which, in turn, can be used to recreate the image.
Early on during the digital imaging process, the picture information is not in color as the image sensors basically only capture brightness. They can only record grayscale information—that is, a series of increasingly darker tones ranging from pure white to pure black. Thus, the digital camera must infer certain information about the picture in order to derive the color of the image. To infer color from this black and white or grayscale image, digital cameras use color filters to separate out the different color components of the light reflected by an object. Popular color filter combinations include, for instance, a red, green, and blue (RGB) filter set and a cyan, magenta, and yellow (CMYK) filter set. Filters can be placed over individual photosites so each can capture only one of the filtered colors. For an RGB implementation, for example, one-third of the photo is captured in red light, one-third in blue, and one-third in green. In such an implementation, each pixel on the image sensor has red, green, and blue filters intermingled across the photosites in patterns designed to yield sharper images and truer colors. The patterns vary from company to company but one of the most popular is the Bayer mosaic pattern, which uses a square for four cells that include two green on one diagonal, with one red and one blue on the opposite diagonal.
Because of the color filter pattern, only one color luminosity value is captured per sensor pixel. To create a full-color image, interpolation is used. This form of interpolation uses the colors of neighboring pixels to calculate the two colors a photosite did not record. By combining these two interpolated colors with the color measured by the site directly, the original color of every pixel is calculated. This step is compute-intensive since comparisons with as many as eight neighboring pixels is required to perform this process properly. It also results in increased data per image so files get larger. In order to generate an image of quality that is roughly comparable to a conventional photograph, a substantial amount of information must be captured and processed. For example, a low-resolution 640×480 image has 307,200 pixels. If each pixel uses 24 bits (3 bytes) for true color, a single image takes up about a megabyte of storage space. As the resolution increases, so does the image's file size. At a resolution of 1024×768, each 24-bit picture takes up 2.5 megabytes. Because of the large size of this information, digital cameras usually do not store a picture in its raw digital format but, instead, apply compression technique to the image so that it can be stored in a standard-compressed image format, such as JPEG (Joint Photographic Experts Group). Compressing  images allows the user to save more images on the camera's “digital film,” such as flash memory (available in a variety of specific formats) or other facsimile of film. It also allows the user to download and display those images more quickly.
During compression, data that are duplicated, or which have no value, is eliminated or saved in a shorter form, greatly reducing a file's size. When the image is then edited or displayed, the compression process is reversed. In digital photography, two forms of compression are used: lossless and lossy. In lossless compression (also called reversible compression), reversing the compression process produces an image having a quality that matches the original source. Although lossless compression sounds ideal, it doesn't provide much compression. Generally, compressed files are still a third the size of the original file, not small enough to make much difference in most situations. For this reason, lossless compression is used mainly where detail is extremely important as in x-rays and satellite imagery. A leading lossless compression scheme is LZW (Lempel-Ziv-Welch). This is used in GIF and TIFF files and achieves compression ratios of 50 to 90%.
Although it is possible to compress images without losing some quality, it is not practical in many cases. Therefore, all popular digital cameras use a lossy compression.
Although lossy compression does not uncompress images to the same quality as the original source, the image remains visually lossless and appears normal. In many situations, such as posting images on the Web, the image degradation is not obvious. The trick is to remove data that is not obvious to the viewer. For example, if large areas of the sky are the same shade of blue, only the value for one pixel needs to be saved along with the locations of where the other identical pixels appear in the image.
The leading lossy compression scheme is JPEG (Joint Photographic Experts Group) used in JFIF files (JPEG File Interchange Format). JPEG is a lossy compression algorithm that works by converting the spatial image representation into a frequency map. A Discrete Cosine Transform (DCT) separates the high- and low-frequency information present in the image. The high-frequency information is then selectively discarded, depending on the quality setting. The greater the compression, the greater the degree of information loss. The scheme allows the user to select the degree of compression, with compression ratios between 10:1 and 40:1 being common. Because lossy compression affects the image, most cameras allow the user to choose between different levels of compression. This allows the user to choose between lower compression and higher image quality, or greater compression and poorer image quality.
One would think with present-day digital technology and scale, one could create a digital camera that is extremely small and portable, particularly since a digital camera is not constrained by the physical constraints of traditional photographic film. This is not the case today, however. As it turns out, the whole process of capturing light and generating a color digital image, such as with a digital camera, is a very compute-intensive process. Further, the resulting images stored at digital cameras today are comparatively large (e.g., image size of one-half megabyte or more is common), thus making it unattractive to download images using wireless (e.g., cellular phone) transmission. The process of recording an image on photographic film, in comparison, relies on straightforward chemical reactions, all without the need for computing resources. A digital image, however, entails a process of converting light into electrical signals, converting those electrical signals into digital or binary information, arranging that information into a visual representation, applying various digital filters and/or transformations, interpolating color from that representation, and so forth and so on. The process of rendering a meaningful digital picture is a compute-intensive undertaking, roughly equivalent in processing power to that required today for a desktop workstation, yet done so within the confines of a handheld portable device.
The upshot of this substantial processing requirement is that, paradoxically, digital cameras today are relatively bulky devices since they require relatively large batteries to support their processing needs. This is easily seen today in camera designs. For instance, digital cameras by Sony employ large custom lithium batteries. Other camera designs employ four to six AA batteries—a fairly bulky arrangement. Even with all those batteries, digital cameras today have relatively short battery lives, such that the digital camera user is required to change out batteries at frequent intervals. Perhaps the biggest drawback of such an approach, however, is the added bulk imparted to the camera itself with such a design.
Today, most of the weight of a digital camera is attributable to its batteries. Thus, present-day digital cameras, been constrained by their battery requirements, are generally no smaller or portable than their non-digital counterparts (e.g., standard 35 mm camera). And the smallest cameras today still remain film-based cameras, not digital ones, due in large part to the battery constraints of digital cameras.
Current approaches to reducing camera size have relied on improvements to the underlying silicon (e.g., microprocessor) technology. For example, one approach is that of increased integration, such as using custom chip sets that are specialized for digital cameras. Examples include, for instance, products offered by Sierra Imaging of Scotts Valley, Calif. and VLSI Vision Ltd. of Edinburgh, Scotland. The basic goal is to decrease a camera's energy requirements by super-integrating many of the digital camera's components onto a single chip, thereby realizing at least some energy savings by eliminating energy requirements for connecting external components. Another approach is to rely on ever-improving silicon technology. Over time, as silicon technology evolves (e.g., with higher transistor densities), ever-increasing compute power is available for a given energy ratio. Either approach does not address the underlying problem that a compute-intensive process is occurring at the digital camera, however. Moreover, the approaches do not address the problem that large image sizes pose to wireless transmission. As a result, the improvement afforded by increased integration or improvements in transistor density provide incremental improvement to camera size, with little or no improvement in the area of wireless transmission or downloading of images.
Moreover, as silicon technology improves, a competing interest comes into play. The marketplace is demanding better image quality and better image resolution. To the extent that improved silicon technology becomes available, that technology by and large is being applied to improving the output of digital cameras, not to decreasing their power requirements (and thereby their size). The net result is that improvements to silicon technology have resulted in better resolution but little or no change in camera size.
Another approach is to focus on improving the underlying image compression methodology itself, apart from the other aspects of image processing. For instance, one could envision a better compression technique that reduces computational requirements by reducing the amount of image data (e.g., using “lossy” compression methodology) substantially more than is presently done. Unfortunately, efforts to date have resulted in images of relatively poor quality, thus negating improvements to resolution afforded by improved silicon technology. Although future improvements will undoubtedly be made, such improvements are—like those to silicon technology—likely to be incremental.
Given the substantial potential that digital imaging holds, there remains great interest in finding an approach today for substantially decreasing the size of digital cameras and improving the downloading of images, particularly in a wireless manner, but doing so in a manner that does not impair image quality. In particular, what is needed is a digital camera that allows users to enjoy the benefits of digital imaging but without the disadvantages of present-day bulky designs with their lengthy image download transmission times. The present invention fulfills this and other needs.
The current technology of digital cameras limits the user's ability to quickly take several pictures. This is because the post-snapshot compression of each picture requires more time than may be desired. As previously described, the camera's compression of the luminosity record of the captured image is a computationally-expensive process. If the compression process immediately follows the image capture and is completed in a single-tasking environment, it would tie-up the resources of the camera, resulting in an unacceptably long delay before the user could take another picture. On the other hand, if the compression processing were postponed while the user continued to take a quick series of pictures, both the RAM and flash memory capacities of the camera would be exhausted.
Alternative attempts to address this problem basically involved adding hardware and/or more implementation-specific algorithms. These attempts require more utilization of battery energy and processor resources, and therefore add weight, size, and cost to the camera device. Accordingly, a better solution is desired.